Exploiting Social Tagging Profiles to Personalize Web Search

Vallet, David; Cantador, Iván; Jose, Joemon M.

doi:10.1007/978-3-642-04957-6_54

Cited by 5 publications

(1 citation statement)

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“…Tags can be viewed as the description of a user. Then, the user profile can be represented in Vector Space Model [25, 26]. To produce accurate tag-based user profiles, selecting suitable candidate tags and inferring their weights are the major focus.…”

Section: Literature Reviewmentioning

confidence: 99%

Profiling users with tag networks in diffusion-based personalized recommendation

Mao

Lü

et al. 2016

Journal of Information Science

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This study explores new ways of tag-based personalized recommendation by relieving the assumption that tags assigned by a user occur independently of each other. The new methods profile users using tag co-occurrence networks, upon which link-based node weighting methods (e.g. PageRank and HITS) are applied to refine the weights of tags. A diffusion process is then performed upon the tag-item bipartite graph to transform the weights of tags into recommendation scores for items. Experiments on three datasets showed improvements of the proposed method over the tag-based collaborative filtering in terms of precision and recall in the datasets with dense user-tag networks and in terms of inter-diversity in all datasets. In addition, the user-tag network is found to be a necessary instrument for the improvements. The findings of this study contribute to more accurate user profiling and personalized recommendations using network theory and have practical implications for tag-based recommendation systems.

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Section: Literature Reviewmentioning

confidence: 99%